Improving genetic algorithms for protein folding simulations by systematic crossover

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Item Type:	Article
Title:	Improving genetic algorithms for protein folding simulations by systematic crossover
Creators Name:	Koenig, R. and Dandekar, T.
Abstract:	To improve protein folding simulations, we investigated a new search strategy in combination with the simple genetic algorithm on a two-dimensional lattice model. This search strategy, we called systematic crossover, couples the best individuals, tests every possible crossover point, and takes the two best individuals for the next generation. We compared the standard genetic algorithm with and without this new implementation for various chain lengths and showed that this strategy finds local minima with better energy values and is significantly faster in identifying the global minimum than the standard genetic algorithm.
Keywords:	Protein Folding, Gentic Algorithm, Systematic Crossover, Lattice Model, Search Strategy
Source:	Biosystems
ISSN:	0303-2647
Publisher:	Elsevier
Volume:	50
Number:	1
Page Range:	17-25
Date:	April 1999
Official Publication:	https://doi.org/10.1016/S0303-2647(98)00090-2
PubMed:	View item in PubMed

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